Provides a comprehensive and updated study of GARCH models and their applications in
finance, covering new developments in the discipline This book provides a comprehensive …

Estimation of time-varying covariances is a key input in risk management and asset
allocation. ARCH-type multivariate models are used widely for this purpose. Estimation of …

This paper studied the effect of the bifurcation of Bitcoin on its interactions with its substitute,
Litecoin. We applied the Granger causality test and a BEKK-MGARCH model to investigate …

Multivariate GARCH (MGARCH) models need to be restricted so that their estimation is
feasible in large systems and so that the covariance stationarity and positive definiteness of …

This paper introduces a new class of multivariate volatility models which is easy to estimate
using covariance targeting, even with rich dynamics. We call them rotated ARCH (RARCH) …

We establish the strong consistency and the asymptotic normality (CAN) of the variance-
targeting estimator (VTE) of the parameters of the multivariate CCC-GARCH (p, q) …

We consider inference and testing in extended constant conditional correlation GARCH
models in the case where the true parameter vector is a boundary point of the parameter …

A spatiotemporal approach is proposed for modeling risk spillovers using time-varying
proximity matrices based on observable financial networks and a new bilateral Multivariate …

Joint estimation of market and estimation risks in portfolios is investigated, when the
individual returns follow a semi-parametric multivariate dynamic model and the asset …

We propose semiparametric CUSUM tests to detect a change-point in the correlation
structures of nonlinear multivariate models with dynamically evolving volatilities. The …